1. Field of the Invention
The present invention relates to a method, apparatus, and program for discriminating the states of subjects, for example, within frames of digital temporal series images that include the subjects, by employing a plurality of types of state classifiers to classify and discriminate the states thereof.
2. Description of the Related Art
Various methods have been proposed to discriminate the states of subjects within digital images (hereinafter, simply referred to as “images”).
For example, Japanese Unexamined Patent Publication No. 2004-259215 discloses a method for discriminating the directions in which faces included in images are facing. In this method, human faces are designated as predetermined subjects, and the directions in which the faces are facing are designated as the states of the subject. Templates are prepared for each direction that the faces face, and the directions in which the faces are facing are discriminated by template matching.
As another example, S. Lao, et al. disclose a method for discriminating the directions in which faces are facing within images, in “Fast Omni-Directional Face Detection”, Meeting on Image Recognition and Understanding, July 2004. In this method, human faces are designated as predetermined subjects, and the directions that the faces are facing are designated as the states of the subject. Classifiers for judging whether judgment target images include faces facing in predetermined directions are prepared for each direction that the faces face, and the directions in which the faces are facing are discriminated thereby.
The aforementioned image discriminating methods assume that the states of subjects to be discriminated are discriminated from within still images. Accordingly, in the case that the states of predetermined subjects are to be discriminated from within temporally sequential images, such as a plurality of frames obtained by video imaging, the same process is executed for each image.
However, there are correlations among the states of predetermined subjects within temporally adjacent images. In the aforementioned methods, these correlations are ignored. Therefore, efficiency is poor and discrimination takes time, which is not favorable, particularly during real time processing.